ML_Simulator is a fully customizable Machine Learning IDE that empowers you to design, train, and test neural network models through an intuitive drag-and-drop interface. Built using Python and PyQt5, the IDE provides a visual environment for creating complex models with ease—ideal for both rapid prototyping and in-depth experimentation.
- Drag-and-Drop Model Creation: Build your neural network by visually connecting nodes.
- Customizable Components: Create and modify nodes with customizable settings such as activation functions, biases, and neuron counts.
- Interactive Network Visualization: Watch your network come to life with real-time updates as connections are made and weights are randomized.
- Training and Evaluation: Train your models using built-in backpropagation and feedforward routines, with support for both SGD and Adam optimizers.
- Dynamic UI Elements: Enjoy a polished, interactive UI that lets you add training data via a table interface, adjust node settings, and toggle between different visual representations.
Open your terminal and execute:
git clone https://github.com/YourUsername/ML_Simulator.git
cd ML_SimulatorInstall the necessary packages by running:
pip install -r requirements.txtTo launch ML_Simulator, simply run:
python3 main.pyOnce started, use the drag-and-drop interface to add nodes, set up network connections, and train your machine learning models interactively.
- Real-Time Training Visualization: Add live training updates to monitor progress as the model learns.
- Prebuilt Model Templates: Integrate templates for popular architectures such as CNNs, RNNs, etc.
- Model Export/Import: Enable features for saving and loading trained models for future use.
- Enhanced UI/UX: Continuously refine the interface to boost usability and performance. TODO
Contributions are welcome! To get involved:
- Fork the repository.
- Create a feature branch.
- Submit a pull request with your enhancements.
This project is licensed under the MIT License. See the LICENSE file for details.
